radailogy pixelshine blog may 2021 III

Leverage AI to extend the clinical utility of your CT scanner

What if you could improve the diagnostic quality and utilization of your existing CT scanners without incurring the high cost associated with replacing them and refurbishing the CT suite? Using Deep Learning technology PixelShine can automatically enhance and harmonize the image quality of studies acquired by any CT scanner at the lowest possible dose – extending the life of older scanners and deferring costly and disruptive replacement projects. You find this exceptional opportunity on our AI platform Radailogy. It has a substantial impact on the traditional revenue stream of hospitals and imaging providers.

radailogy pixelshine blog may 2021 II

Harmonize CT Image Quality

New deep learning CT scan processing software is now available through Radailogy that can help everyone overcome the limitations of Iterative Reconstruction. PixelShine from AlgoMedica automatically improves the quality of any CT scan by reducing image noise without reducing the conspicuity of fine details. It improves the image quality of CT studies acquired at any dose level, to make lower dose scanning possible for all CT studies. In addition, PixelShine is vendor neutral; so it works with all CT scanners, regardless of the vendor, including older and refurbished systems.

radailogy pixelshine blog may 2021 I

Radailogy proudly presents PixelShine: Why this new AI has an impact on CT radiation dose

The cumulative effect of the exposure to CT imaging compounds the need to achieve the lowest per-scan patient dose possible. While low-dose CT imaging techniques exist, there is often a compromise that must be made in both image quality and cost. Lower-dose studies have higher image noise, which results in lower quality images, which are more difficult to analyze. Iterative Reconstruction (IR) is still the most used technique for improving the quality of lower-dose imaging studies. However, IR can take substantially longer to process images and is prone to producing images with a waxy or blurry appearance if applied too strongly on low-dose studies. Deep Learning CT Processing (DLCP) is the next generation in CT image noise reduction techniques. DLCP not only improves CT images acquired during typically low-dose procedures like lung screening and pediatric exams, but it also presents the ability to significantly reduce radiation exposure for other higher-risk categories such as oncology and obese patients. In addition, it can improve the image quality of ultra-low-dose abdominal, cardiac, and brain scans. Radailogy presents PixelShine by AlgoMedica in order to assist to the reduction of CT radiation dose and from now on to substantially improve image quality in low dose CT studies.

Radailogy: Detecting fractures on X-rays

Radailogy: Detecting fractures on X-rays

 

Not only trauma centres and radiology institutes, but every doctor has to deal with the diagnosis of fractures. X-rays are still the first line modality, especially for peripheral skeletal trauma. Radailogy offers you a new CE approved app from the French company AZmed: Rayvolve. Either let Rayvolve process your X-ray images always in the background, or send us selected images with a specific question. Rayvolve has been trained on data sets of one million trauma images. AZmed gives Rayvolve a sensitivity of 96% and a specificity of 86%. In our own test series, Rayvolve performed as follows: Sensitivity 93%, Specificity 86%, PPW 92%, NPW 89%, Accuracy 91%. In a multicentre study, Rayvolve provided a time saving of 36% and an increase in specificity of 8%.
Rayvolve is proving to be a valuable aid for doctors in daily practice: whether the app is used occasionally, for example in doctors’ surgeries, or whether it is used to optimise the workflow in medical centres.
The best way to request Rayvolve is with our Radailogy services Defained or Pure AI. Register, upload and get started!
Info at www.radailogy.com